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README.md

@@ -24,10 +24,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.8362147406733395
+      value: 0.941747572815534
     - name: F1
       type: f1
-      value: 0.803921568627451
+      value: 0.9285714285714285
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,12 +37,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the stool-image dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3833
-- Auroc: 0.9133
-- Accuracy: 0.8362
-- Sensitivity: 0.82
-- Specificty: 0.8475
-- F1: 0.8039
+- Loss: 0.4076
+- Auroc: 0.9357
+- Accuracy: 0.9417
+- Sensitivity: 0.8864
+- Specificty: 0.9831
+- F1: 0.9286
 
 ## Model description
 
@@ -74,8 +74,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Auroc  | Accuracy | Sensitivity | Specificty | F1     |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|:-----------:|:----------:|:------:|
-| 0.4174        | 0.98  | 100  | 0.4700          | 0.8665 | 0.7916   | 0.7753      | 0.8060     | 0.7775 |
-| 0.3544        | 1.96  | 200  | 0.4304          | 0.8706 | 0.8179   | 0.7247      | 0.9005     | 0.7890 |
+| 0.4127        | 0.98  | 100  | 0.4406          | 0.8789 | 0.8100   | 0.7472      | 0.8657     | 0.7870 |
+| 0.3473        | 1.96  | 200  | 0.4249          | 0.8774 | 0.8074   | 0.7247      | 0.8806     | 0.7795 |
 
 
 ### Framework versions

all_results.json

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+    "train_samples_per_second": 20.937,
+    "train_steps_per_second": 1.314
 }

eval_results.json

@@ -1,13 +1,13 @@
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 }

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train_results.json

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trainer_state.json

@@ -1,6 +1,6 @@
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+  "best_model_checkpoint": "./stool-condition-classification\\checkpoint-100",
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